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Reference guide to build inventory management and forecasting solutions on AWS

AWS Big Data

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. To take advantage of this data and build an effective inventory management and forecasting solution, retailers can use a range of AWS services.

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Smart Factories: Artificial Intelligence and Automation for Reduced OPEX in Manufacturing

DataRobot Blog

This “revolution” stems from breakthrough advancements in artificial intelligence, robotics, and the Internet of Things (IoT). In this example, I walk through how a manufacturer could build a real-time predictive maintenance pipeline that assigns a probability of failure to IoT devices within the factory.

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Deep dive into the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

Let’s look at some key metrics. After analyzing YARN logs by various metrics, you’re ready to design future EMR architectures. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. Jiseong Kim is a Senior Data Architect at AWS ProServe.

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Introducing the AWS ProServe Hadoop Migration Delivery Kit TCO tool

AWS Big Data

The results of the log analyzer reveal Hadoop workload insights with various views and metrics of the Hadoop applications shown in Amazon QuickSight dashboards, which leads to the design of a future EMR cluster. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services.

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Improve power utility operational efficiency using smart sensor data and Amazon QuickSight

AWS Big Data

Data collection and processing are handled by a third-party smart sensor manufacturer application residing in Amazon Virtual Private Cloud (Amazon VPC) private subnets behind a Network Load Balancer. The AWS Glue Data Catalog contains the table definitions for the smart sensor data sources stored in the S3 buckets.

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The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure

DataKitchen

Here are a few examples that we have seen of how this can be done: Batch ETL with Azure Data Factory and Azure Databricks: In this pattern, Azure Data Factory is used to orchestrate and schedule batch ETL processes. Azure Blob Storage serves as the data lake to store raw data. Azure Machine Learning). So go ahead.

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Build Hybrid Data Pipelines and Enable Universal Connectivity With CDF-PC Inbound Connections

Cloudera

In the second blog of the Universal Data Distribution blog series , we explored how Cloudera DataFlow for the Public Cloud (CDF-PC) can help you implement use cases like data lakehouse and data warehouse ingest, cybersecurity, and log optimization, as well as IoT and streaming data collection.